34 results about "Noise floor" patented technology

This application discloses a wind tunnel-based noise detection method, apparatus, storage medium, and electronic device. The method includes: when testing a test piece in a wind tunnel, acquiring a measured noise spectrum in the testing environment and obtaining the operating frequency of the wind tunnel's inverter; matching the background noise spectrum corresponding to the operating frequency in a background noise spectrum library based on the operating frequency; aligning and dividing the measured noise spectrum and the background noise spectrum using a frequency band division rule adapted to the inverter's operating frequency to obtain multiple frequency band units; based on the acoustic energy density of the measured noise spectrum and the background noise spectrum within each frequency band unit, extracting the energy component corresponding to the background noise spectrum from the measured noise spectrum through directional orthogonal projection, and reconstructing the spectrum of the residual energy after extraction to obtain the effective aerodynamic noise spectrum of the test piece; and calculating the noise detection result of the test piece based on the effective aerodynamic noise spectrum.

A wireless device is configured to transmit radar signals at extremely low spectral density so that the receiver can be operated at the same time without saturating and thereby enabling full-duplex operation. To achieve sufficient range, beamforming is used together with a very long correlation time for detection of the radar signal, in which case the receiver can resolve backscattered or reflected radar signals far below the noise floor, while the bandwidth of the transmitted radar signal can be very high. The wide bandwidth enables the wireless device to maintain a low power spectral density while increasing output power, and also increase the depth resolution. The extremely low power spectral density even in the transmission beam direction makes the probability that communication will be disturbed very low. The high bandwidth calls for digital filters for both transmitted and received signals to equalize the radar frequency response characteristics of the radio unit.

This invention discloses a magnetotelluric denoising method and system based on a physics-driven and conditional diffusion model, belonging to the field of electromagnetic signal processing technology. This method integrates the advantages of neural networks and the physical characteristics of magnetotelluric signals, and proposes a physics-driven synthesis strategy based on statistical priors of measured source data and a curriculum-based dynamic physics-driven noise addition strategy based on training progress factors. Addressing the scarcity of high-quality, clean samples, a clean background field that highly approximates real physical characteristics is synthesized using a parametric mathematical model. The introduction of curriculum-based dynamic physics-driven noise addition (such as noise floor annealing, square wave incrementing, and morphological clustering pulses) accurately simulates natural background degradation and complex human interference, enabling the model to adapt to extremely complex time-frequency characteristics under different geological structural backgrounds. This completely overcomes the domain shift problem caused by static Gaussian white noise training, constructs a richer sample library, and lays the foundation for accurate denoising of conditional diffusion models.

This application discloses a method and product for self-diagnosing external interference. The method includes: acquiring the inherent parameters of the frequency-using terminal to calculate the theoretical noise floor; measuring the total received power in real time and calculating the super-noise power accordingly; when the super-noise power exceeds a preset power threshold, acquiring the baseband demodulation quality parameters of the current channel; and performing correlation discrimination based on the super-noise power and baseband demodulation quality parameters. When the super-noise power is high and the demodulation quality is below a preset threshold, it is determined to be external interference; otherwise, it is determined to be a strong useful signal. This application establishes a two-dimensional causal correlation model between physical layer power and baseband layer quality within the terminal, enabling real-time and objective self-diagnosis of external interference from the terminal's own perspective, thus improving the objectivity, timeliness, and accuracy of the diagnosis.

This invention belongs to the field of noise floor reduction and proposes a frequency-band noise floor reduction method based on a spectrum analyzer. This invention can solve the problems of uneven noise power distribution and excessive noise power estimation. It includes the following steps: acquiring the noise floor signal of the spectrum analyzer, wherein the noise floor signal is a low-pass or band-limited white noise signal with a specified bandwidth; dividing the specified bandwidth into a first number of sub-segments and dividing the signal power before denoising into a first number of sub-segments; estimating the noise power under the specified bandwidth and dividing it into a first number of sub-segments; denoising each sub-segment and calculating the noise power spectral density of each sub-segment after denoising based on the bandwidth after segmentation, the signal power before denoising after segmentation, and the estimated noise power after segmentation; and ensuring that the noise power spectral density after denoising is not negative by using the compression factor method or the square root method.

The application relates to a dual cascade flow type processing method and system for removing artifacts from myoelectric signals and reconstructing the signals, and relates to the technical field of biomedical signal processing.The method comprises the following steps: extracting a standard stimulation artifact template from a noisy calibration myoelectric signal, calculating a decision threshold and a frequency domain noise floor baseline; transversely splicing a myoelectric signal data block with historical data in a time domain residual artifact cache, and performing artifact identification and cancellation based on the standard stimulation artifact template and a morphological gating mechanism; sending a time domain processing signal into a frequency domain splicing cache, performing fast Fourier transform after reaching a preset window length; dynamically generating a probability mask according to the frequency domain noise floor baseline, performing inverse fast Fourier transform, and obtaining a single-frame recovered signal; and obtaining a smooth and continuous reconstructed myoelectric signal by using an overlap-add method; and on the premise of not depending on high-performance hardware, accurate cancellation of stimulation artifacts is realized, and real physiological signals are protected.

The application provides a howling suppression method, a sound pickup terminal and a howling suppression system, which are applied to the sound pickup terminal. The method comprises the following steps: monitoring the distance between the sound pickup terminal and a collection terminal in real time; if the distance is less than a preset distance threshold, performing howling suppression according to a first howling suppression strategy; if the distance is greater than or equal to the preset distance threshold, performing noise floor detection and howling detection to obtain a noise floor detection result and a howling detection result, performing howling suppression according to a second howling suppression strategy according to the noise floor detection result, and / or performing howling suppression according to a third howling suppression strategy according to the howling detection result, so as to improve the howling suppression effect and reduce the timbre distortion degree.

This invention provides a method for processing echo signals from a fish finder, the fish finder itself, and a storage medium, comprising: S1, receiving an echo signal; S2, performing envelope processing on the echo signal to obtain an envelope signal; S3, calculating the variance of data within a selected sliding window until a signal segment with a variance value less than a predetermined variance threshold is found; S4, determining the noise floor value of the envelope signal based on the average amplitude of the found signal segment; S5, determining the starting position of a weak signal data segment based on the location of signal points with amplitudes less than the noise floor value; S6, performing partial filtering on the envelope signal to obtain the image signal to be displayed, and performing IIR filtering or FIR filtering on the weak signal data segment; signal segments other than the weak signal data segment retain their original values. Using the above technical solution, weak signals in the echo signal can be identified, thereby improving the sensitivity of the fish finder.

This application discloses a method for fabricating a PIN-structured perovskite X-ray detector, belonging to the field of detector technology. The method includes: providing a conductive substrate; pre-treating the conductive substrate to obtain a pre-treated conductive substrate, wherein the conductive substrate is ITO glass; fabricating a hole transport layer on the pre-treated conductive substrate, the hole transport layer comprising a NiOx thin film; fabricating a perovskite absorption layer on the hole transport layer, the perovskite absorption layer comprising a perovskite single-crystal thin film; fabricating a composite electron transport layer on the perovskite absorption layer, the composite electron transport layer comprising a thin film and a thin film; fabricating a metal electrode on the electron transport layer; and encapsulation. This method, through the composite p-i-n band structure, narrow window control of perovskite layer thickness and doping, and low-resistance contact design of the composite electrode, can achieve higher effective signal output, lower dark current and noise floor, and faster transient response at lower operating bias voltages, thereby improving detector sensitivity, reducing the detection limit, and improving detection accuracy.

This invention discloses a method, system, medium, and device for detecting DC arc faults. The method includes: acquiring line current signals, performing feature processing to obtain feature values, and saving the average value of the features within a preset time period as initial feature values; filtering effective frequency bands whose noise floor values ​​meet set conditions based on the noise floor values ​​of each feature frequency band using a frequency band selection method; calculating arc energy values ​​to obtain dynamic arc energy and static arc energy; and detecting DC arc faults: when both dynamic arc energy and static arc energy exceed their respective thresholds, and the number of DC arc occurrences within a preset time period reaches a preset number, a DC fault arc is detected; otherwise, it is detected as normal. This invention is applied to DC fault arc circuit breakers, which can significantly improve the accuracy and reliability of DC arc detection and reduce the risk of false positives and false negatives in DC arc detection.

The present disclosure provides a distance sensor calibration method, device, electronic equipment and readable storage medium, the method comprises: determining the noise floor value of the first distance sensor according to the ranging parameter collected by the first distance sensor when the first distance sensor is not blocked by an obstacle; determining the first calibration parameter of the first distance sensor according to the ranging parameter collected by the first distance sensor when the distance between the first distance sensor and the obstacle is within a first preset distance range; and determining the second calibration parameter of the first distance sensor according to the noise floor value, the first calibration parameter and a preset coefficient. The present disclosure can obtain all calibration parameters of the first distance sensor through two acquisition calibration processes and one calculation process, thereby improving factory calibration efficiency and distance sensor production efficiency, and reducing production cost.

This invention discloses an environmental acoustic adaptive sound effect control method, relating to the field of sound effect control. By integrating three modes—manual calibration, intelligent inspection, and event triggering—it can not only respond to user commands but also automatically trigger calibration when the speaker moves, there are sudden changes in environmental noise, playback mode switches, or a preset cycle is reached. This ensures that the speaker can proactively optimize the sound effect in a timely manner after changes in the usage environment, maintaining the speaker's sound effect at a suitable listening level. By quickly judging the suitability of the environment, it first assesses the background noise level, and only performs subsequent acoustic feature analysis when the environment is suitable for measurement. This avoids ineffective or even harmful calibration in high-noise environments, improving the reliability of system decisions and the accuracy of the final sound effect adjustment.

This invention introduces a method for noise reduction in radio frequency links based on spectrum cancellation. The specific steps are as follows: S1: Signal modeling and acquisition; S2: Spectrum analysis and frequency band division; S3: Noise floor gain estimation and quantization calculation of raised noise power; S4: Spectrum cancellation and splicing processing; S5: Effect evaluation. This invention captures the statistical characteristics of noise floor in real time by referencing the frequency band and dynamically estimates the noise floor gain of the target frequency band. It can flexibly adapt to the time-varying characteristics of noise floor under different interference scenarios and achieve accurate tracking and elimination of noise floor without manual intervention. For the transition frequency band, a linear weighted cancellation strategy is adopted, which effectively avoids the spectrum jump and signal distortion problems caused by traditional hard threshold processing or fixed filtering, ensuring a smooth transition of the signal spectrum after processing and fully preserving the detailed features of the target signal. It has good suppression effects on various typical and complex interferences such as aiming interference, jamming interference, sweeping interference, and comb spectrum interference.

The application belongs to the field of analog integrated circuit design, and particularly relates to a redundant current range current steering DAC based on digital pre-distortion. The application carries out rotation correction through an improved DEM decoding circuit, measures and quantizes error codes corresponding to the static mismatch error of each current unit, and reduces the circuit area and the influence of additional circuit parasitic on the DAC speed without additional control circuit. A redundant current unit is introduced at the highest bit to expand the quantization range, and the error code and clipping problem introduced by DPD correction are solved. Only a simple algorithm of a 14-bit adder and a 14-bit subtractor is needed to directly operate on binary codes, and a secondary decoding is used to realize thermometer code addition operation compatible with DEM, so that the timing delay and circuit complexity of the thermometer code addition circuit are greatly reduced. The circuit timing delay of the application meets the speed requirement of high-speed and high-precision current steering DAC, and compared with DEM correction only, the application significantly improves the SFDR without raising the noise floor.

The application discloses a kind of silicon-based mach-zehnder modulator optimal linear point search method.The method is according to the power estimation of the fundamental component and third-order intermodulation component of modulator output signal to estimate the linearity of corresponding operating point, and the optimal linear point of the modulator can be obtained based on the maximum estimated value of linearity. The method uses maximum entropy spectrum subtraction to reduce the noise floor of the signal, and uses brute force search method to search for the optimal combination of the phase difference between the upper and lower arms of the modulator and the reverse bias voltage to obtain the optimal operating point. Compared with the linearity obtained by setting the modulator operating point to the quadrature point in the conventional linearity test method, the optimal linear point searched by the method can significantly improve the linearity of the modulator, which is beneficial to realize high linearity silicon-based integrated microwave photonic system.

This invention discloses an online defect detection method in the fabrication process of silicon carbide chips, specifically relating to the field of semiconductor defect detection technology. The method adaptively adjusts laser parameters based on the quality of real-time acquired photoluminescence signals to excite hidden defects and generate characteristic signals. Time-resolved spectral acquisition of the signals is performed, and background noise and self-absorption effects are decoupled using a nonlinear separation model to extract hidden defect features. The signal distribution and noise floor are monitored in real-time, and the discrimination threshold is dynamically adjusted to obtain candidate defect regions and their characteristics. Different detection modes are sequentially activated, and the most sensitive excitation method is selected to confirm the defect type, density, and location. This invention adaptively adjusts laser parameters based on the quality of real-time acquired photoluminescence signals, enabling stable excitation of hidden defects under dynamic conditions. By decoupling background noise and self-absorption effects, pure defect feature signals are extracted. Dynamic adjustment of the discrimination threshold and fusion of three detection modes achieve high-confidence defect identification.

The application discloses an electromagnetic spectrum anomaly signal detection method and system, and relates to the technical field of electromagnetic spectrum detection. The method performs continuous spectrum scanning on a target frequency band and carries out time sequence alignment to construct a spectrum data set. A sliding window is set, and statistical analysis is performed on the spectrum data to establish a noise floor benchmark representing background noise level. The overall spectrum energy change in the window is combined to compensate for receiver gain drift, and a net spectrum representation relative to the noise floor is formed. On this basis, the time-frequency units continuously enhanced in the spectrum are connected and aggregated to generate candidate events. Multidimensional features are extracted from the event level, the decision threshold is adaptively adjusted according to the spectrum occupation state, and the candidate events are comprehensively judged, so that stable detection and reliable identification of abnormal signals in a complex electromagnetic environment are realized.

This invention relates to the field of fiber optic temperature sensing technology, and discloses a distributed fiber optic temperature sensing low-noise demodulation method, system, device, and medium. The method includes real-time acquisition of Stokes and anti-Stokes light intensity data from a fiber optic temperature monitoring system; averaging the Stokes and anti-Stokes light intensity data to obtain Stokes average intensity and anti-Stokes average intensity, respectively; applying noise floor correction to the Stokes average and anti-Stokes average intensities to obtain Stokes corrected intensity and anti-Stokes corrected intensity; performing dispersion compensation based on the Stokes corrected intensity and anti-Stokes corrected intensity to obtain Stokes compensated intensity; and demodulating the temperature based on the Stokes compensated intensity and anti-Stokes corrected intensity to obtain the temperature monitoring result. This invention eliminates inherent random noise and signal misalignment through averaging, noise floor correction, and dispersion compensation, thereby improving temperature measurement accuracy.

This invention belongs to the field of wireless ranging and positioning technology, specifically relating to a star-flash SLE phase ranging method based on average excess delay and the Rician K factor. The invention first constructs a bidirectional channel frequency response (CFR), maps it to a complex frequency domain sequence, and performs an IFFT to obtain the channel impulse response, constructing a power-delay distribution (PDP). Then, noise floor estimation and denoising are performed, followed by extraction of average excess delay, RMS delay spread, and Rician K factor estimates to form a joint discriminant index characterizing multipath and non-line-of-sight (NLS) levels. A dynamic peak value threshold is generated based on the joint discriminant index, the earliest valid path satisfying the dynamic threshold is selected, and the corresponding distance estimate is output. Compared with the traditional fixed-threshold complex-valued distance estimation (CDE) phase ranging method, this invention can suppress systematic deviations caused by misselection of strong reflection paths under strong multipath / NLS conditions, improving ranging accuracy and robustness, and is suitable for deployment on resource-constrained microcontroller platforms.

A wearable audio device including an acoustic driver, a feedforward microphone, a feedback microphone, and a controller is provided. The controller generates an aware audio signal based on a playback audio signal and an external audio signal corresponding to the feedforward microphone. The controller further generates a feedback path signal based on the aware audio signal and a feedback audio signal. The feedback audio signal corresponds to the feedback microphone. The controller further generates a noise floor reduction signal based on the feedback path signal, the playback audio signal, and the external audio signal. The controller further generates an acoustic driver signal based on feedback path signal and the noise floor reduction signal. The controller renders, via the acoustic driver, output audio based on the acoustic driver signal.

Embodiments of the present invention provide an adaptive filtering method, apparatus, electronic device, readable storage medium, and chip. The adaptive filtering method includes: acquiring range-Doppler matrix data of a millimeter-wave radar; determining a noise floor threshold for at least one range segment based on data from multiple consecutive frames; determining a point cloud effectiveness rate; determining an adaptive constant false alarm rate (CFAR) parameter for the current frame based on the point cloud effectiveness rate corresponding to historical frames; performing two-dimensional detection based on the adaptive CFAR parameter and the noise floor threshold for the current frame to determine an original point cloud; filtering invalid point clouds from the original point clouds corresponding to multiple consecutive frames to determine an optimized point cloud; identifying the scene corresponding to the optimized point cloud and determining false target features in the scene; and filtering the false target features in the optimized point cloud to determine a filtered point cloud. The solution of the present invention improves the accuracy of target detection by millimeter-wave radar.

The application provides a stator lamination burr online early warning method and system based on acoustic emission spectrum analysis. The method comprises obtaining an effective acoustic emission signal sequence based on spindle phase trigger interception. A hardware DC bias elimination operation is performed on the effective acoustic emission signal sequence to generate a zero mean sequence. Boundary symmetric continuation and discrete wavelet decomposition are performed on the zero mean sequence to obtain a specific level of detail coefficient vector set. The full-band absolute energy of the zero mean sequence and the high-frequency absolute energy of the detail coefficient vector set are calculated in parallel. A single-cycle hardware multiplication is performed on the full-band absolute energy based on an early warning proportionality coefficient and a noise floor prevention constant to generate a dynamic absolute energy threshold. The high-frequency absolute energy is compared with the dynamic absolute energy threshold to output an alarm trigger flag. The application eliminates the delay jitter caused by software scheduling, realizes microsecond-level deterministic response and pre-interception in high-speed stamping scenarios.

This invention discloses a method and system for detecting abnormal signals in the electromagnetic spectrum, relating to the field of electromagnetic spectrum detection technology. The method constructs a spectrum dataset by performing continuous spectrum scanning and timing alignment on the target frequency band; it sets a sliding window and performs statistical analysis on the spectrum data to establish a noise floor benchmark characterizing the background noise level, and compensates for receiver gain drift by incorporating overall spectral energy changes within the window, forming a net boost spectrum representation relative to the noise floor; based on this, it connects and aggregates continuously enhancing time-frequency units in the spectrum to generate candidate events, extracts multi-dimensional features from the event level, and adaptively adjusts the decision threshold based on the spectrum occupancy status to comprehensively judge the candidate events, thereby achieving stable detection and reliable identification of abnormal signals in complex electromagnetic environments.

The application discloses a MEMS resonant accelerometer based on coupled synchronization, a tuning module is arranged around a mass block, frequency and sensitivity of two accelerometers are matched through a bias voltage, so that the frequency difference remains consistent under different measurement inputs. In the state of mutual coupling and electric synchronization, the device using the method of the application can maintain the synchronization state to a greater extent and has no sensitivity attenuation phenomenon. The application effectively solves the problem of narrow synchronization bandwidth of the coupled synchronization accelerometer, and significantly widens the measurement range of the whole machine. In addition, the noise in the oscillation loop in the synchronization state is significantly suppressed, so that the noise floor of the sensor is further reduced, and the zero bias instability is further improved.

This invention discloses a method for detecting ultra-shortwave broadband satellite signals based on superimposed spectrum and deep learning. Firstly, this invention enhances the distinction between ultra-shortwave signals and noise floor through spectrum superposition, while suppressing the influence of short burst interference, effectively improving signal characteristics under low signal-to-noise ratio conditions. Simultaneously, it proposes an ultra-shortwave signal feature extraction backbone network, SST-Backbone (SC-ST-Backbone), which integrates multi-layer convolutional layers and a four-layer SC (shortcut)-ST (Swin Transoformer) layer. The SC-ST module in the backbone network incorporates the global focus advantage of the Transformer, combined with a residual multi-layer convolutional module focusing on local features to increase the network depth and receptive field. This enables the network model to more accurately detect broadband ultra-shortwave signals in the target frequency band, efficiently removing noise floor interference while reducing focus on anomalous signal features, improving the detection accuracy of broadband ultra-shortwave target signals in complex environments, and reducing the false alarm rate.

Techniques are provided for radar blanking using dynamic subinterval noise floor estimation. A radar blanking system implementing the techniques according to an embodiment includes a noise floor estimator configured to extract noise samples from a segment of in-phase (I) and quadrature (Q) input signal samples. The system also includes a blanking threshold calculator configured to calculate blanking thresholds based on statistics of the noise samples, the statistics including a mean of the noise samples and a standard deviation of the noise samples. The system further includes a blanking processor configured to select a subset of the IQ input signal samples that exceed the blanking thresholds and replace the selected subset of the IQ input signal samples with the mean of the noise samples to generate a blanked signal.

The application relates to the technical field of telecommunications and Internet of Things, and particularly relates to a multi-protocol communication resource optimization scheduling method for power Internet of Things, which acquires bandwidth demand indexes, power consumption constraint indexes and current spectrum data of a target terminal, quantitatively calculates protocol matching degrees of multiple candidate communication protocols to determine a target communication protocol; constructs an interference evaluation model in combination with a basic noise floor, adjacent frequency band signal strength and frequency offset, optimally selects target spectrum resources; and simultaneously processes multi-terminal competition based on a task priority mechanism, adaptively corrects bandwidth weight coefficients and power consumption weight coefficients in protocol matching degree calculation, and transfers the updated weight coefficients to the next round of scheduling. The application solves the contradiction between high-definition video backhaul bandwidth demand and battery endurance constraint in a power Internet of Things operation site, ensures stable transmission of key services, reduces device energy consumption, improves anti-interference capability, and improves the robustness and stability of the power Internet of Things.

Techniques are provided for radar blanking using dynamic subinterval noise floor estimation. A radar blanking system implementing the techniques according to an embodiment includes a noise floor estimator configured to extract noise samples from a segment of in-phase (I) and quadrature (Q) input signal samples. The system also includes a blanking threshold calculator configured to calculate blanking thresholds based on statistics of the noise samples, the statistics including a mean of the noise samples and a standard deviation of the noise samples. The system further includes a blanking processor configured to select a subset of the IQ input signal samples that exceed the blanking thresholds and replace the selected subset of the IQ input signal samples with the mean of the noise samples to generate a blanked signal.